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[Music] welcome everyone uh we have a very special guest here today with us Toby carile uh Welcome to our uh talk at Google at author series uh he’s going to be talking about his new book deep value why activist investors and other contrarians battle for the control of losing corporations uh Toby has a unique perspective on U uh value investing much like Google’s uh his approach to Value investing is data driven just like Google’s approach to engineering uh in his book he uses statistical analysis and in-depth research to give evidence for a simple yet counterintuitive idea losing stocks with failing businesses and uncertain Futures can sometimes offer unusually attractive investment uh potential uh his work in this area is very much like Ben Graham’s classic work uh in his 1934 security analysis book um the funny thing about Classics is everyone’s heard about them very few people have actually read the classics uh Toby uh is one of those rare uh few individuals investors I would say who’s been living and breathing uh Ben Graham’s deep value investing philosophy so please help me welcome uh Toby carile thank you oh yeah you hi folks uh thank you very much for having me here today I’m very much looking forward to speaking to Google just a little bit about me my name is Tobias carile I’m the managing director of eum investment management and I manage the fund and some separately managed accounts my most recent book is deep value and before that I I published uh qu qu itative value uh co-authored with a gentleman who did his quantitative research through Booth I blog at Greenback and I’m just launching a new site called the acquires multiple that uh is yet to go live The Talk today proceeds in four parts the first part we’re going to discuss is the philosophy of deep value um what it is its Genesis um then we’re going to look at some of the behavioral reasons that stocks become undervalued in contrarians at the gate third we’re going to examine some ways that we can avoid making those behavioral errors that create undervalued stocks and finally we’re going to examine a simple metric for generating outstanding returns in the market in uh 1927 a 33-year-old Benjamin Graham started teaching a night class at Colombia that he called security analysis he offered practical counsel for the students who took the class but the thrust of what he taught was that a security had an intrinsic value and it was distinct from its market price which you could observe on the stock market in any given day and he argued that when there was a sufficient mispricing either the price was at a discount to the intrinsic value or in some instances where the price was at a premium to the intrinsic value you could trade long or short and rely on the fact that would be some mean reversion to bring the price back to intrinsic value in 1929 the stock market had its worst crash it continues to be the worst crash to date from its peak to its trough it fell almost 90% in 1932 fully 3 years after the bottom of that crash the stock market still hadn’t recovered um Graham authored a series of articles for Forbes Magazine where he pointed out some research that he had undertaken that said that of the 600 issues on the stock market at that time 200 of them traded for less than their liquidation value so they traded for less than what the shareholders in those companies could get out of them if they wanted to wind them up and then a sizable portion of those traded at a discount to their net cash backing which is after paying out all of the liabilities of the company there would still be cash lift in a bank account and you could buy the entire company for less than that amount and he said um he likened it to corporate gold dollars being traded for 50 cents or less with strings attached and that sort of enduring iconic image continues to be the way that we think about value investing that it is an attempt to buy 50 Cent dollar some years later um John B Williams added some additional color to the way that we go about valuing a company and that is to look at all of the cash INF flows and outflows discount them back to the present day and that gives you an intrinsic value so as you um hunt in the market for these particular stocks you can find those at the the greatest discount to intrinsic value will tend to underperform and those at the greatest premium to intrinsic value will tend to sorry will tend to underperform so this this chart shows if we rank every stock in the universe and this is a global universe so 22,000 positions if we give them all a ranking price to cash flow Price to Book price to earnings we take the average of those and then we rank them into five groups the glamour quintile which is the most expensive T to underperform on average and the value quintile which is the cheapest tends to out perform so when we’re seeking to invest in these companies one thing that we can observe is that price tends to fluctuate more than intrinsic value which only moves much more slowly and so when you find these occasional moments when there’s a large discount or a large premium you can invest to capture that discount the question that I’m often asked is what is it that causes the discounted price to return to its intrinsic value and it’s a question that Benjamin Graham got when he was he was uh appearing before a senate committee in 1955 and the chairman said how do you close that Gap is it by advertising or or what happens and Graham gave one of his great answers where he said it’s a mystery and it’s a mystery to him as it is as much of a mystery to him as it is to everybody else but we understand it to me mean reversion and so what this talk is about is what are the actual mechanics of mean reversion what are the things that make mean reversion occur so this is actually Graham’s list so he talks about in one that’s just general Improvement in the industry and this is a very uh common occurrence that the industry is in a trough the business is in a trough it’s got a period of bad luck perhaps some bad management and either the incumbent managers turn the company around or external managers are brought in less commonly a sale or a merger or some sort of liquidation sometime later behavioral researchers debont and ther examine Securities on the basis of a variety of different metrics but they’re looking particularly in this case for undervaluation and overvaluation measured by Price to Book value so they found that by selecting the desile which is one10 of stocks that were most undervalued and the desile of stocks that were most overvalued and then examining the trend in earnings per share you find this unusual uh phenomenon where the earnings for the most undervalued stocks have been falling for the years previous to the portfolios being formed and for the most overvalued stocks they’ve been in increasing and that’s the reason that one is overvalued and the other is undervalued but then this very unusual thing happens once the portfolios are formed the overvalued stocks still continue to grow but they slow a great deal and the earnings per share of the undervalued stocks begin to improve at this stage and four years hence on average the undervalued stocks which have been selected simply based on their undervaluation have actually earned more and are earning more than the overvalued stocks which had the the highest rate of growth it’s a phenomenon that we see over and over again in the research so this is another interesting study subsequent to the debont and failer research by lonik Scher and vishne they said well if it is in fact the case that there is this mean reversion in the fundamentals of the business if there’s mean reversion in the earnings if the undervalued stocks do start creating earnings growth and the overvalued stocks earnings slow then what if we went and selected portfolio specifically on we could find an undervalued portfolio with very slow growth an overvalued portfolio with very high growth and an undervalued portfolio with very high growth which would be the better portfolio so they divided they sorted the universe into three portfolios on the basis of valuation from most overvalued to the median average and to the most undervalued and then they divided each of those portfolios into the highest rate of growth the mid rate of growth and the slowest rate of growth so there were nine portfolios formed I’ve selected three of them here to show you the um to show you the phenomenon so the glamour portfolio has the highest rate of growth and you can see in earnings cash flow Book value operating earnings all of those are growing higher than the other two value portfolios but you can also see that you have to pay a higher multiple to acquire these stocks so they’re 19.6 * 10.8 time cash flow they’re expensive Ive stocks on the other end of the scale these are the two value portf these are two of the three value portfolios the high growth value portfolio is still growing at quite a high rate of growth but it’s available for a much cheaper multiple and the contrarian value portfolio which is the very low growth portfolio growing at a low rate and available on a low multiple so as you’d expect as you would expect the Value Port folios outperform the glamour portfolios but this is the really interesting thing the low growth undervalued portfolio outperforms the high growth undervalued portfolio and this is something really unusual and I think it’s something that is a little bit counterintuitive because we sort of like to think that high growth undervalued stocks are Bargains gems in the rough and it turns out that mean reversion acts on those portfolios as well to pull the high growth back and to improve the low growth so this is just that previous slide with the glamour portfolio removed just so we can see specifically and the thing that I want to draw your attention to here is that the contrarian value portfolio in many of these categories is actually a little bit more expensive than the high growth portfolio the reason possibly is that earnings are a little bit more anemic cash flows a little bit more anemic so you can see on the book value basis the high growth value portfolio was slightly more expensive expensive but it’s very definitely growing much faster than the contrarian value portfolio so the real driver of returns here was the undervaluation and not the the rate of growth and then there was some mean reversion as well which pushed down the high rate of growth and made the value the high growth value less attractive over a period of time compared to the contrarian value this was a an earlier examination conducted by Michelle Clayman there was a book written by Tom Peters that came out in the early ‘ 80s called in search of excellence and Peters said that he’d identified the characteristics that um created excellent companies and he looked at a variety of these sort of quantitative uh Financial type elements the book has been described as the book of the century possibly by Tom Peters himself but I’ve never read it but I’ve read this the research and the research is compelling these are his criteria for an excellent company so they have very high rates of asset growth very high rates of equity growth they’re expensive and they have excellent Returns on Capital assets and Equity so Clayman said well let’s create let’s create the opposite portfolio let’s call them un excellent companies and we’re going to find those with the worst asset growth Equity growth low valuation anemic Returns on Capital equity and assets and then we’re going to track their performance over a period of time so the thing that I draw your attention to is just the valuation alone and you can see here this is some research that appears in the book it was conducted by Barry Bannister at stifle Financial the UN excellent portfolios have vastly outpaced the excellent portfolios for for an early period of time and it’s difficult to see on this chart the excellent portfolios did actually outperform the market but not since you get a better return investing in the S&P 500 than you do investing in these very high quality high growth companies these excellent companies and you get a much better return investing in the ugliest of the ugly the question that naturally people ask when they see that data is well is there some advantage to investing in the excellent portfolios because they offer some sort of risk protection is it a is it a downside protection um phenomenon is it that when the world go into a recession you want to be in these things that that generate higher rates of growth and the answer is no um banister looked at periods where the Glo Global growth was below average and above average so above the line is when the shaded areas where global economic growth is below average and the the lighter areas where global economic growth exceeds the average and you can see quite clearly there’s no real um method to when when un excellent outperforms or excellent out or excellent outperforms it does outperform occasionally but it doesn’t necessarily need a bad state of the world world to do so so I always like to use this Motif to sort of describe the nature of what occurs in these undervalued companies most companies are going to go through this cycle there are a very small number of companies that can avoid this cycle but very small number of them this is uh from a woodcut from uh Albert Duro in 1494 from a book called The Ship of Fools which is about some fools on a ship to a Fool’s Paradise and they go through they have a number of folies and one of them is um huous about where they are and disregarding the role of luck in their own lives good and bad so the wheel is it’s the Wheel of Fortune that’s Fortune’s hand puppeting the wheel in the top leftand Corner the the ass at the top is Reno Iran and you can see that he’s at the very Pinnacle and he’s about to descend down the other side but instead he reaches out for the Sun and this is what in the academic Financial literature they describe as naive extrapolation you imagine that your current state will continue on when in actual fact mean reversion is a much more likely outcome so the next Ravi ired he’s slowly turning back into a man he descends down the other side and this is perhaps where deep value investors want to stake their claim s Reno I am without a kingdom he’s not even visible on the on the wood cut and then back up the other side Ren yabo I will reign maybe that’s another good time to invest too so if what we’re looking for is fundamental weakness declining earnings and undervaluation the thing that makes them difficult to buy for other investors makes it equally difficult for us to buy so how can we avoid making the behavioral errors that other investors are making how can we not be the naive extrapolation investor and become the contrarian value investor that captures that upside performance from buying companies with ugly fundamentals there’s been a great deal of research into this area of um the role of statistical prediction models and experts it’s it’s a counterintuitive um area of study for this reason so a a professor went and studied a thousand admissions to Hospital of depression or psychosis and apparently on initial presentation they can appear very similar and there’s a subsequent diagnosis several weeks or months later where it’s able to they’re able to determine properly whether the patient who presented was in fact psychotic or depressed so he created by examining ing the admission records and the subsequent diagnosis he created a a simple questionnaire that could be administered by um psychologists when these people presented to the hospital and they could make a determination so without the benefit of the model the worst psychologists got it right about 55% of the time on average about 62% and the very best psychologists got it right 67% of the time the simple model in back test got it right 70% of the time the professor distributed the questionnaire to a variety of different psych psychologists in in the hospital to basically they were inexperienced who were students and then there were clinical psychologists who were actually um treating patients and they found that without the benefit of the model the inexperienced students got it right about 59% of the time the experienced clinical psychologists got it right about 64% of the time the inexperienced psychologist with the benefit of the model but the ability to override the model’s output got it right about 2/3 of the time and the experienced psychologists with the benefit of the model got it right 75% of the time but this is the really incredible thing the simple model by itself itself outperformed all of them and the reason is that we make errors when we attempt to apply a model and we don’t follow the model’s output and that leads us to underperform what the simple model does by itself the reason that people when people observe this uh research they often say if you have a case that’s so different from the base rate from the statistical uh research that you’ve conducted doesn’t it make sense then to be able to override the model and the example they always give you have some sort of algorithm that predicts whether John will go to the theater on Friday and now you know that he has a broken leg shouldn’t you be able to factor that into your model to determine whether he will in fact go to the theater this Friday and the answer is no and the reason is that we tend to find more broken legs than they really are and particularly in this type of deep value investing all of the stocks have what appear to be broken legs you might be familiar with the little book that beats the market it’s a book by Joel green blood he um took Warren Buffett’s exhortation to follow wonderful to buy wonderful companies at fair prices and he translated that into a quantitative model that we’ll come we’ll we’ll examine in detail in a moment but for the moment you just need to know that it meant high quality however that’s defined and good value he had a experiment in the um in his own firm where he handed out lists of the stocks selected by the formula and he allowed people to either CH in their own separately managed accounts to either choose the stocks that they wanted or to have him apply the formula automatically he found that the automatically applied formula did in fact outperform the market over 2 years and by quite a substantial margin he also found that when people were allowed to manage the portfolio themselves they tended to underperform and the reason is that they Cherry Picked out the very best stocks and they were the stocks that looked the ugliest so you might say well they were not experts they were people who were relying on his expertise but then greenblat says we attempted to do the same thing and he found he had the same outcome he underperformed his own model so that brings us to the Golden Rule of statistical prediction rules and that is that simple models outperform experts but simple models continue to outperform experts even when they have the benefit of the model when we’re thinking about designing a quantitative system there are several things that we need to be uh aware of one of them is that the rules must be simple and they must be concrete they must be simple so they’re able to be followed and concrete so that they’re able to be understood this is uh um a picture of a pipe this is not in fact a pipe this is a picture of a picture of a pipe and when we’re valuing companies in many ways this is sort of what we’re doing we’re we’re using some proxy and there are a variety of different models or proxies that we can select we can choose the liquidation value we can look at the franchise value the growth value earnings power value the acquire as multiple we can use any any number of these simple multiples and but we’re not really getting the truth of the company and so it’s important that we recognize first that there are limitations to the model and recognizing that the model is somewhat imperfect we can recognize then that we do have some tool for making a decision so the 8020 rule does apply to information in investing too you get 80% of the way there with a simple model and the urge of most investors is to continue to find that final bit of information that will remove the uncertainty that they have but often by the time that occurs the uncertainty has been removed for everybody else as well and so those low prices that you were attracted to are gone so the simplest rule I think and one of the most effective is the net current asset value rule um Graham wrote about this in 1934 he described it as a rough measure of liquidating value so you can see you look simply at the balance sheet you ignore the earnings the cash flow statement it didn’t exist at the time that Graham put this together but you could ignore it for the purpose of this analysis and then you treat only the current assets as having as having value so cash is worth cash receivables there’s some discount applied to them inventories would depending on whether it’s food that can spoil fashion High fashion that will be less valuable in 12 months time or something that’s going to be continue continue to be valuable well into the future and then you can look at the fixed assets and determine whether they have a value the research shows quite comprehensively that net current asset value massively outperforms for such a and it’s an extraordinary thing that is such a simple analysis so the market in these instances is always a small capitalization micro capitalization equivalent to what we’re looking at for the net current asset value stocks and you can see in the US that’s a study from the 197 1970 to 1983 the net current asset value portfolio did 29% versus 115% for the market this is a study that I conducted in in the US 83 to 2010 just continuing on the second study so it was a second uh 27 7 years and uh similar sort of outperformance maybe more so which is surprising because you would think that with all of the access to information that a lot of these positions would have been arbitraged away but they haven’t been they continue exist to exist in the UK and they exist globally as well but there are some unusual things that you find when you conduct this sort of research the first one is that the individual net current asset Value stock is is more likely to go to zero than the rest of the market and the rate is about 6% for a net current asset Value stock versus 2 a half% for the average stock in the market but as a portfolio there are fewer down years than the market and this is perhaps the most controversial finding the most counterintuitive and that’s that loss making net Nets actually outperform net Nets that are profitable within the profitable net Nets those that don’t pay a dividend outperform the ones that do pay a dividend so your instinct might be to find a net net that pays a dividend and with positive earnings and that would lead you to underperform what you can do just by n Nets alone so many of you will know that Warren Buffett started out as a student of Benjamin Grahams then he worked with him in his new uh Graham Newman Corporation and then he went out and he set up his own partnership and his in the early days of his partnership he was very much a Graham type investor looking at liquidation value the first position one of the early positions that he put into the fund was sandborn map it had a portfolio of Securities and it was trading at 65 cents on the dollar of that portfolio of Securities with no value given at all to the business which was making about $100,000 a year he got on the board he got control he liquidated the security portfolio paid it out in a tax effective Manner and so he got a 50% return just on the portfolio and then the business remained and the business continues to exist to this day as a geographic information system business in the US he had this Evolution after meeting Charlie Munga and in 1963 he found American Express m in a scandal so American Express is a financial company and it had provided some Warehouse receipts to Anthony Tino deangelus who was a Commodities broker and Trader and he had figured out that he could bring soybean oil to the port show the inspectors that his tanks contained soybean oil and then through pipes and valves he could fill up with seawat what had been soybean oil then they would check a new tank and it would contain the old soybean oil at one stage he controlled almost 10 times more uh soybean oil than there was in existence and that was the secret to his low low prices he um eventually he went bankrupt American Express had said that the warehouses did in fact contain the salad oil his broker went bankrupt when the people who had lent against those Warehouse receipts came looking for some Deep Pockets they found American Express and American Express owed something in the order of $175 million which was 10 times its average annual earnings over the last few years so there was a real risk that American Express would go bankrupt at that stage Buffett put 40% of his portfolio into the into the stock it recovered he bought $13 million worth of that stock that position today if he had held it which he he didn’t all the way through because he’s changed investment entities but that that position today is worth something in the order of 14 billion which is an enormous return so he learned from that that if wasn’t necessary for these things to have a liquidating value he could in fact buy them on the basis of a franchise he made sure that people were still continuing to use American Express cards and so it taught him that there was a different method of investing so in 1972 he found seiz candies um it was earning something like $2 million on $8 million of invested Capital they paid $27 million for it he assessed the value were in the order of $45 million so he got a fairly substantial discount and he said at the time when someone asked him about it are you still a gry Amite type investor he said I’m 85% Graham 15% Phil Fisher who recommended the scuttlebutt method of investing which is you go and find as much information as you can about the quality of the business and its ability to grow so ciz candies between 1972 to 2011 returned $1.35 billion to Burkshire Hathaway which they continue to invest and it’s required only something like $70 million reinvested in the business to generate those earnings so that’s what’s known as a franchise the lesson that he took from investing in Seas candies was that you’re much better off with these businesses that are able to grow over a long period of time he said though the cigar butt might have a single puff lift in it and that puff is pure profit after you’ve after you’ve smoked that puff there’s nothing left so he stopped being a sarot investor and he became an investor in wonderful companies at fair prices looks at Buffett’s investment methodology and says that’s an that’s been very lucrative for a very long period of time assuming that we don’t have Buffett’s great mind are we just able to create a quantitative version of the methodology that Buffett describes in the little book The in in his letters and he wrote a book about that process and so he decided that good quality as defined by Buffett means a high return on invested Capital so invested capital is what it actually costs to run what you the money that you need invested in the business to run the business the assets of the business that are actually used to produce income the higher the return on invested Capital the better the business the faster it’s able to grow and for valuation he uses an earnings yield uh earnings before interest in profit interest in taxes because it’s um it’s it’s agnostic to the capital structure where interest payments on debt affect the tax that you pay if you back out interest in tax then you get this idea of the operating earnings that are coming into the business we tested this in quantitative value and we found that the magic formula does in fact beat the market a comparable Market of stocks and quite comprehensively it’s baten it by three and a half% each year from 1974 to 2011 what is really shocking is that the earnings yield alone what I describe as the acquir as multiple beat the magic formula itself and the quality measure actually underperformed the market the quality measure was the actually led the magic formula to wanted to perform the the earnings yield alone and it’s not just a performance it’s just it’s not just a raw return story it’s in fact a risk adjusted return story as well the earnings yield alone generates a better sharp ratio and a better sortino ratio which is basically the amount of growth relative to the amount of variability in the returns so you get better returns and you get better risk adjusted returns just using the earnings yield and the reason is that there is this mean reversion in return on invested Capital so Michael mbison has tested this he’s examined a number of the the Thousand largest listed stocks in the US ranked them on on the in order of return on invested capital and then divided them into five groups so the very highest and then he’s ranked them into very highest and the Very lowest and then he’s examined those same companies 10 years hence and what he finds is that the highest return on invested capital mean reverts towards the mean return and the lowest return on invested Capital also slightly improves so I think of the highest return on invested Capital as being Reno at the very peak of the wheel and S CER Reno at the very bottom of the wheel so what is the aquiris multiple well it’s the Enterprise multiple the reason it’s called the acquires multiple is it’s the metric used by leverage buyout firms private Equity firms activists to look through through into the hidden value of the business and in terms of the mechanics of it it’s market capitalization plus debt because the business has to fund the debt you’re able to use the stock you’re able to use the cash to pay off the debt you’re also liable for the preferred stock you’re also liable for any minority interests and underfunded pensions off balance sheet liabilities so it’s the real cost to buy the business and then you get access to ebit D or ebit which is the cash flow coming in it turns out that it’s it doesn’t really make much difference which you choose but when we tested them using data from 1964 to 2011 so we tested a variety of different um possible metrics earning field which is the inverse of the price earnings metric just to highlight the two the acquir is multiple using ebit the acquires multiple using ibit da free cash flow on Enterprise Value gross profits yield so that’s just revenues Minus cost of goods sold to give you the third line on the income statement and book to Market which is the inverse of Price to Book so that they’re arranged in the same way we found that the acquir is multiple outperformed and again not just on a raw return basis it outperforms on a risk adjusted return basis too and comprehensively the four things that I want to take away from today are that the very deepest undervalued stocks outperform the highest quality and the highest growth even in the undervalued portfolio so undervalued portfolios divided into high growth and low growth the low growth undervalued portfolios will outperform so it’s better to be assuming that there’s going to be some me reversion positive and negative rather than to naively extrapolate out the growth in earnings simple models applying these ideas will always outperform expert discretion so at the beginning of your process you decide what is important in the assessment of value and then you rigorously apply that without fear or favor and the acquires multiple is the best multiple if you’re looking for a very simple application a very simp simple rule this is a very good one it’s a plug for the book so I go into these studies in a great deal more depth in the book um each one of them there are several different versions of the study so you can see as we go through the entire book the site acquires multiple has a um a place to capture your email and your details if you’d like to learn more when it’s up and going it’ll basically provide a free screen of of acquires multiple companies and um some commentary and some research as it goes along so if you have any questions I’d be happy to hear them uh this question is about the mean reversion and uh amongst the universe of companies do you think there are some particular companies or industries that are more uh more I mean uh flexible towards mean reversion and others that are not or do you or do do you think it’s the entire universe that just mean revers are there there there are certainly some companies do demonstrate persistence in their ability to maintain a high return on invested capital and um the question is is that if if you look at a large enough Universe of stocks would you just expect that there would be no persistence at all would you find some just by random chance so it’s not entirely clear whether the there’s a reason for their persistence or whether it’s just the luck of looking at a 10-year period um mson has looked at that specifically and he found that um Pharmaceuticals and pharmaceuticals and biotechnology and another group did sort of demonstrate some mean some persistence so they kept the high returns and invested Capital but he wasn’t able to determine the factors that so prospectively if you look at a data set without knowing the outcome can you determine which ones are going to persist and which ones are going to mean of it and he hasn’t been able to do that yet uh you mentioned that like uh the ibit divided by E is is actually better than the magical the than the magical formula is Jo green back aware of that I cannot imagine that he doesn’t know that right it doesn’t make a lot of sense to me he’s almost certainly aware of that and but you know you you think he knows that but he he still put roic into the book well the magic formula does outperform the the magic formula does beat the market yeah but I’m sure that he also he also done the St he also has done the study uh on the separate metrix right do you do you think he hasn’t done that uh I’m sure that he has but but okay okay I okay I guess so why do it that way well yeah you know there understand my question yeah I do there there are elements to the business it’s a marketing business as much as it’s a a return business but I have the impression that greenl doesn’t really I mean he has enough money and he doesn’t really care about making more money I mean I I could be wrong in different states of the world different um the magic formula will outperform the earnings yield so when the markets are racing up in a bull market it’s about even but there are some periods of time the late 1990s for example which was an unusual period in the markets but the magic formula did outperform the pure earnings yield but the earnings yield has outperformed the magic formula over the last 15 years so it may be a um it may be a job security type idea that if you apply the magic formula rather than the earnings yield you you have fewer years of underperformance when I test that that’s not what I find basically the earnings yield outperforms the magic formula pretty consistently and pretty consistently over 5 and 10 year Rolling periods I think it’s the better metric for the reason that I’ve sort of outlined here that return on invested capital mean reversion is a very real phenomenon and it’s an easily explained phenomenon when you find companies that are very profitable it invites competitors to go into those Industries and industries that are low return people leave the industry that that happens all the time that’s happening right now in the oil and gas industry with uh low rates of return because the oil price is so low they’ll stop drilling holes so that that has a flow on effect Joel greenblat talks about the fact that a lot of these economical companies are too cheap and don’t have enough liquidity for the fund managers to own and also that the a lot of the fund managers just want salable product that’s the the the popular names and so on so could you comment on um the the liquidity issue and moving in and out of some of these smaller issues um the the book The Little book that beats the market shows a return for the magic formula that’s much higher than you can achieve if you adjust for liquidity and for size but you can still get outperformance applying it in a very large capitalization universe and market capitalization weighted which means you size the positions in the portfolio relative to the market capitalization of the company that you’re buying rather than equally waiting them so that means that you’re putting more money into the bigger companies so you you sort of that is testing for precisely that I see problem so the the results that I was showing in here were actually market capitalization weighted so you get slightly better results again if you equal weight for the simple reason that you’re putting more money into smaller positions mhm so market capitalization waiting sort of adjusts for that the the problem with something like the net current asset value is that it’s really not an investable strategy for anybody other than an individual they’re just not around often enough and they’re not big enough or liquid enough to sort of invest in you know if you have a million dollars of investable capital it’s probably too small for you but the magic formula and the acir as multiple scale beautifully you can take the acir as multiple in an S&P 500 Universe select the 5% or the 10% so the 25 or 50 stocks in that Universe roll it once a year and you’ll find pretty consistently that you get quite a lot of of out performance doing that so um as a broad problem liquidity and size are issues that reduce returns but these metrics still do work in large universes you just get the you get you get the incredible outperformance if you’re able to invest in the little stuff which small managers and and individuals can does that does that very good answer thank you so I think your last statement has answered a lot of my questions I was going to ask but uh for the magic formula back test I would like to know the more details so one is you said the rebalance is once per year yes okay so how uh how does the back test deal with the survival buyers that’s a good question so the database that we use compy stat mhm keeps companies that have failed in the data so if it failed in 1975 the back tester would have bought it in it could have bought it in 1974 because the data remains in the database so we do a number of things we in in quantitative value we outline in some detail the process that we go through to back test basically we do a number of things like we lag the data so one of the problems that you have is that you have this look ahead bias which is the possibility for trading on information that you don’t already have so we and in addition to that you have this January effect which is quite pronounced so there’s some tax loss selling at the end of the year and then if you invest assuming that you can buy your entire position on the very first day of January you capture quite a bump in performance so what we did is we rebalanced the portfolios on June 30 okay and we used data from the preceding December so we used the K data mhm and we rebalanced in in June so we were avoiding that January effect and we were avoiding the look ahead bias and then we use a very good out of Bas so so uh the basket is about 30 30 stocks in the basket it varies so depending on the size of your Universe the Universe um and depending on the size of how how much you’re investing and how much time you want to spend doing it the the fewest stocks that you could possibly do it with might be 20 okay and the most stocks you really don’t get get much benefit Beyond about 30 so somewhere between 20 and 30 is um is the appropriate size for a portfolio equally weighted and that also means that you can buy them on a quarterly basis so you might buy you know if you’re buying 20 you buy five on a quarterly basis mhm and then you rebalance those five 12 months and one day to capture the tax effect or okay does that make sense okay yeah thank you uh so if like more people use the same strategy would then your strategy just be equals to the market possibly but Joel greenlet wrote that book in 2006 the magic formula doubled the return of the stock market last year so the magic formula has continued to work and the reason that it continues to work is that there aren’t that many value investors out there it’s a niche strategy and within that Niche strategy the Deep value investment is a niche strategy most guys who are value investors would try to emulate Buffett their their um franchise type investors there are very few guys who are really deep value guys um and there’s also this problem that you’ll find and if you if you look at the data I’ll so I’ll give these positions away for free on the aquiris multiple.com and you can go there and you’ll be able to see they’re quite frightening positions you’ll be buying very cheap iron ore mining companies you’ll be buying very cheap oil and gas companies a few years ago you would have been buying for profit education there frightening to buy and that’s that’s the real um thing that drives the returns that’s why I went that’s why I went through that part of the presentation that says you have to follow the model that’s the most important thing without fear or favor you can’t cherry pick because what you do when you cherry pick is you do what everybody else does and you avoid the things that generate the really big out performance okay I got a follow-up question have you tried the same strategy in different markets yes yes so it the magic formula Works um and I discussed justce in deep value but the magic formula Works in Japan uh it works in the UK and it works in Europe X the UK um in each of those instances the acquires multiple alone outperforms the only place where that hasn’t happened for the period of the data that We examined which was about 14 years because there just isn’t that much international data but uh Japan the magic formula seem to outperform the acquir as multiple alone in that one single region over that 14e period That We examined hey so I was wondering what does your company do then like do you just follow the model as well so basically we have a we have some additional things that we do quantitative value goes through quite comprehensively a a very big model that you could that you could use and we sort of discuss you can do things like um avoiding companies at high risk of financial distress avoiding fraud avoid avoiding earnings manipulators um looking for financial strength looking for quality of earnings so that’s making sure that the um the cash flow into the business matches the accounting earnings all of those things add a little bit of additional performance at the edges but the big muscle movement the Big Driver of performance is the acquires multiple so yes that’s what I do that’s what I apply main question is like then uh why R bin moved to Liquidator to operator is it because he has he had uh too much money and another question is related to the first book of uh Joe greenl like like he’s talk about the uh spinoff and also the special situation I think his point is that uh just buying those would be good but if you can pick your spot remember yeah that would be better I think his his uh performance in 10 years was like 50% that’s the highest I’ve ever know so then like so then uh he’s then his ways like uh this is the area you want to pick from and then you want to pick the best like then it’s kind of uh not the same as what you are saying what we saying here you saying like uh don’t involve uh don’t involve any human being uh just buy everything right uh yeah just want to know you his um his first book you can be a stock market genius which is a terrible name for a really good book the process that he describes in there is reasonably complex investment strategy and it requ and it’s sort of it’s a strategy that really only a human being could Implement at the moment because it requires reading unusual filings and finding spin-offs or companies about to pay out a big dividend special situation investing um I don’t think that he could have invested as much money in that strategy as he can in the magic formula and I think that that’s a more difficult strategy to implement you can certainly get expertise in an area and understand better than another area the spin-offs are special situations are really a very broad basket of potential um things that you can do and you can become good in an industry or or good at a particular thing um and that might lead to better performance I sort of think that the broader your strategies and the broader your potential Universe of stocks the better performance you’re going to have I think to maintain that very high rate of return he was paying out a lot of the capital that he was so he’d make the profit and pay it out and then do it again the next year whereas this is a this is a the magic formula is a compounding strategy you know you roll over whatever you get then you reinvest that compounded amount and it’s a strategy that really shows how good it is over a longer period of time because you get to that point where you you’re investing larger sums of money at a higher rate than the special situation one which requires it you keep on paying it out and you sort of limit it a little bit in where you can apply it question why he why did he change yeah yeah yeah why he change possibly the challenge maybe he had too much money to invest okay so one of the biggest criticism of any model created looking at backward data is you are fitting data right Y and um so the strategy that is outlined feels a bit like Oh Let’s ignore quality and go for the liquidation value or the Enterprise Value or buying price of the company and that could be kind of a valid criticism what would be your answer to that well we’ve looked at it in different markets too so um I certainly didn’t go into it it’s it’s not a great marketing strategy to tell somebody that what we’re going to do is buy the lowest quality stocks that we can find or not really care about quality it’s a much better marketing strategy to go and say what we do is we look for really high quality stocks that are undervalued and that’s what we buy because that sounds like a really safe strategy to me if you say I’m going to ignore quality people think you’re crazy so I’ve written an entire book explaining why I ignore quality so we didn’t sort of set out to find that it was just something that it’s sort of unavoidable in the literature you find this every single time you read and I I’ve sort of I gave a sample of the studies in the book there are a lot more studies in the book there’s another thing that looks at admiration so what are your positive or negative feelings about a company and they rank all of the companies on the basis of how liked or hated they are then they examine their performance over the following year the most hated companies outperform the most admired companies morning star gives rankings to companies this is an a company a plus this one’s a b this one’s a d this one’s an e the E’s comprehensively outperform the A’s every single time you look at research and it’s it’s so uh counter to everything that you see everywhere else where everybody’s saying find the really high quality ones so so um I didn’t go looking for it but when you look at this sort of strategy outside of this Market you find almost the same thing the one exception to that is Japan for whatever reason the magic formula over the period of the data that We examined outperformed the earnings yield alone Japan’s a um an outlier in a number of different strategies momentum hasn’t worked in Japan whereas that’s worked in in lots of other markets um but even though Japan has sort of been gently falling this just an interesting side uh side comment even though it’s been gently falling since 1990 value investing strategies in Japan have worked really well just buying the cheapest companies on the basis of price to earnings price to cash flow Price to Book has done something like 20% a year so the magic formula may have just captured a little bit more of that performance but yes there’s always a risk of data mining in this sort of in this sort of stuff I think that the acquir is multiple is the way that value investors think about investing so you’re if you think about the way that you’re instructed in security analysis or the intelligent investor or any of Buffett’s letters he says think about buying the company in its think about buying the entire business you’re not buying a share of it you’re buying the whole thing and that’s exactly what the acquires multiple does it says this is what you pay for the market capitalization but don’t forget that you’ve got preferred stock debt minority interests off balance sheet liabilities underfunded pensions other things that you have to fund but you do get the benefit of the cash that’s sitting in the bank or the net cash and then you have this discretion to spend the operating earnings as they’re coming in on capex or paying down debt or various other things so it’s sort of it’s looking at the same thing that big acquirers look at and you’re often f i often find that I’m in positions that somebody else has been buying right behind me it’s a car I can’t or another activist or private Equity Firm and something happens in them because when they get very cheap this sort of um there’s a little bit of instability it’s not a situation that should persist like that there they’re sort of inviting external managers to come in and try to rectify the situation so data mining is always a problem but I think there are a variety of reasons why this strategy should work quite well and it does work quite well in different time periods and in different markets Buffett talks about holding stocks for the longterm and one of the reasons that he likes it is because of the tax consequences can you talk a little bit about the difference between trying to find companies that you can hold for a long period of Time Versus rebalancing and um using the Deep value strategy well this is one of the arguments for this is what the franchise investors are trying to do they want to buy that company that can sustain those very high Returns on invested capital and ideally grow and compound away throwing off cash while they’re doing it so that 10 years or 20 years from now you’re sort of getting out of it in dividends what you invest invested in it and it’s a much more valuable company so if you think about the process of going and finding one of those companies knowing that there’s that mean reversion in return on invested Capital what would you rather buy do you want to buy one that has a very high return on invested Capital that might mean revert or are you better off finding one that’s very cheap that might be at a trough that you can hold for seven or eight or N9 or 10 years that reverts up I think you’ve got as much chance of selecting the challenge is not to buy something that looks like it’s high quality now the challenge is to buy something and hold something that is high quality so we all want to buy the same stock maybe I haven’t made that clear enough we all want to I want to buy everybody wants to buy the really high everybody wants to own the really high quality stock the compounding machine that has the very high returns and invested Capital but can you use historical data to identify them it’s not clear but what is clear is that buying the ones with high Returns on invested Capital don’t necessarily turn into ones that have high returns and invested Capital subsequently [Music]